CONFIDENCE.NORM

Quirk found

Category: Statistical · Last tested 2026-09-01

Real compatibility results for the CONFIDENCE.NORM function: executed in Excel for the web, Google Sheets and LibreOffice Calc, with desktop Excel behavior from Microsoft’s official documentation (we do not run desktop Excel — Excel for the web is a different application and is executed separately). Syntax and links to that documentation are below.

Support matrix

Engine	Documented	Live-tested	Verdict
Excel (desktop)	Yes	No — documented only	n/a
Excel for the web	—	Yes (recalc, 2026-09-01)	Supported, behaves as documented
Google Sheets	Yes	Yes (Drive import, 2026-08-31)	Quirk found
LibreOffice Calc	Yes	Yes (25.8.7.3, 2026-08-31)	Quirk found

LibreOffice version history

We executed the same test cases under each LibreOffice release to show exactly when CONFIDENCE.NORM’s support changed — not documentation claims, real results.

LibreOffice version	Verdict	Tested
24.2.0.3	Quirk found	2026-08-31
24.8.7.2	Quirk found	2026-08-31
25.2.0.3	Quirk found	2026-08-31
25.8.7.3	Quirk found	2026-08-31

Why isn't CONFIDENCE.NORM working in LibreOffice?

CONFIDENCE.NORM exists in LibreOffice 25.8.7.3, but it is not a drop-in match for Excel — our executed tests found real behavioral differences (detailed in the test results on this page). If a formula that works in Excel or Google Sheets misbehaves in LibreOffice, compare your usage against the failing cases above before assuming your data is wrong.

Why isn’t CONFIDENCE.NORM working in Google Sheets?

CONFIDENCE.NORM runs in Google Sheets, but our executed cases show it does not match Excel’s documented behavior on every input (the failing cases are listed on this page). If a formula that behaves one way in Excel gives you a different answer in Sheets, compare your usage against those cases before assuming your data is wrong.

Discovered quirks

=ROUND(CONFIDENCE.NORM(A2,A3,A4),9) on Google Sheets returned 0.692951913, but the documented/expected result is 0.692951912.
Provenance
Microsoft's CONFIDENCE.NORM page publishes this example's result rounded to 0.692952; its CONFIDENCE page publishes the identical calculation to more digits as 0.692951912, and the two agree. Independently derived from the documented normal-distribution half-width z_(1-alpha/2) * standard_dev / sqrt(size): scipy.stats.norm.isf(0.05/2) = 1.9599639845400545, so 1.9599639845400545 * 2.5 / sqrt(50) = 0.6929519121748391 -> 0.692951912 at 9 dp. Asserted at 9 dp rather than the page's 6 because the deeper figure is derived, not merely copied; MISMATCH vs expected: expected 0.692951912, got 0.692951913
=ROUND(CONFIDENCE.NORM(A2,A3,50.9),9) on Google Sheets returned 0.692951913, but the documented/expected result is 0.692951912.
Provenance
Excel documents "If size is not an integer, it is truncated", so 50.9 must behave exactly as 50. Independently checked that this discriminates: a genuine size of 50.9 would give 1.9599639845400545 * 2.5 / sqrt(50.9) = 0.686798; MISMATCH vs expected: expected 0.692951912, got 0.692951913
=CONFIDENCE.NORM(1,A3,A4) on LibreOffice Calc returned #VALUE!, but the documented/expected result is #NUM!.
Provenance
Excel documents: "If alpha <= 0 or alpha >= 1, CONFIDENCE.NORM returns the #NUM! error value."; MISMATCH vs expected: expected '#NUM!', got '#VALUE!'
=CONFIDENCE.NORM(A2,-1,A4) on LibreOffice Calc returned #VALUE!, but the documented/expected result is #NUM!.
Provenance
Excel documents: "If standard_dev <= 0, CONFIDENCE.NORM returns the #NUM! error value."; MISMATCH vs expected: expected '#NUM!', got '#VALUE!'
=CONFIDENCE.NORM(A2,A3,0) on LibreOffice Calc returned #VALUE!, but the documented/expected result is #NUM!.
Provenance
Excel documents: "If size < 1, CONFIDENCE.NORM returns the #NUM! error value."; MISMATCH vs expected: expected '#NUM!', got '#VALUE!'

Executed test cases

Excel for the web (executed 2026-09-01 via OneDrive recalculation)

These values come from Excel for the web, not from desktop Excel. They are two different implementations of the calculation engine, and this run measured only the web one: the corpus was uploaded to OneDrive as .xlsx, recalculated by Excel for the web on open, and downloaded again for readback. Excel for the web is a rolling service with no pinnable version, so the run is identified by its date. Where a value here disagrees with the Expected column — which is Microsoft’s documentation of the desktop product — we cannot tell you whether the web engine diverges from the desktop one or the documentation is wrong about both, because we do not run desktop Excel.

Formula	Description	Result	Expected	Verdict
=ROUND(CONFIDENCE.NORM(A2,A3,A4),9)	Microsoft's documented worked example: 95% confidence half-width for a population standard deviation of 2.5 and a sample of 50	0.692951912	0.692951912 Provenance Microsoft's CONFIDENCE.NORM page publishes this example's result rounded to 0.692952; its CONFIDENCE page publishes the identical calculation to more digits as 0.692951912, and the two agree. Independently derived from the documented normal-distribution half-width z_(1-alpha/2) * standard_dev / sqrt(size): scipy.stats.norm.isf(0.05/2) = 1.9599639845400545, so 1.9599639845400545 * 2.5 / sqrt(50) = 0.6929519121748391 -> 0.692951912 at 9 dp. Asserted at 9 dp rather than the page's 6 because the deeper figure is derived, not merely copied	Matched
=ROUND(CONFIDENCE.NORM(A2,A3,50.9),9)	A non-integer sample size, which the documentation says is truncated	0.692951912	0.692951912 Provenance Excel documents "If size is not an integer, it is truncated", so 50.9 must behave exactly as 50. Independently checked that this discriminates: a genuine size of 50.9 would give 1.9599639845400545 * 2.5 / sqrt(50.9) = 0.686798	Matched
=CONFIDENCE.NORM(1,A3,A4)	A significance level of exactly 1	#NUM!	#NUM! Provenance Excel documents: "If alpha <= 0 or alpha >= 1, CONFIDENCE.NORM returns the #NUM! error value."	Matched
=CONFIDENCE.NORM(A2,-1,A4)	A negative population standard deviation	#NUM!	#NUM! Provenance Excel documents: "If standard_dev <= 0, CONFIDENCE.NORM returns the #NUM! error value."	Matched
=CONFIDENCE.NORM(A2,A3,0)	A sample size below 1	#NUM!	#NUM! Provenance Excel documents: "If size < 1, CONFIDENCE.NORM returns the #NUM! error value."	Matched
=CONFIDENCE.NORM("abc",A3,A4)	A non-numeric alpha argument	#VALUE!	#VALUE! Provenance Excel documents: "If any argument is nonnumeric, CONFIDENCE.NORM returns the #VALUE! error value."	Matched

Google Sheets (executed 2026-08-31 via Drive import)

Google Sheets is a rolling service with no pinnable version, so this run is identified by its date. The corpus was imported to Drive as .xlsx, recalculated by Sheets, and exported back for readback.

Formula	Description	Result	Expected	Verdict
=ROUND(CONFIDENCE.NORM(A2,A3,A4),9)	Microsoft's documented worked example: 95% confidence half-width for a population standard deviation of 2.5 and a sample of 50	0.692951913	0.692951912 Provenance Microsoft's CONFIDENCE.NORM page publishes this example's result rounded to 0.692952; its CONFIDENCE page publishes the identical calculation to more digits as 0.692951912, and the two agree. Independently derived from the documented normal-distribution half-width z_(1-alpha/2) * standard_dev / sqrt(size): scipy.stats.norm.isf(0.05/2) = 1.9599639845400545, so 1.9599639845400545 * 2.5 / sqrt(50) = 0.6929519121748391 -> 0.692951912 at 9 dp. Asserted at 9 dp rather than the page's 6 because the deeper figure is derived, not merely copied	Mismatch
=ROUND(CONFIDENCE.NORM(A2,A3,50.9),9)	A non-integer sample size, which the documentation says is truncated	0.692951913	0.692951912 Provenance Excel documents "If size is not an integer, it is truncated", so 50.9 must behave exactly as 50. Independently checked that this discriminates: a genuine size of 50.9 would give 1.9599639845400545 * 2.5 / sqrt(50.9) = 0.686798	Mismatch
=CONFIDENCE.NORM(1,A3,A4)	A significance level of exactly 1	#NUM!	#NUM! Provenance Excel documents: "If alpha <= 0 or alpha >= 1, CONFIDENCE.NORM returns the #NUM! error value."	Matched
=CONFIDENCE.NORM(A2,-1,A4)	A negative population standard deviation	#NUM!	#NUM! Provenance Excel documents: "If standard_dev <= 0, CONFIDENCE.NORM returns the #NUM! error value."	Matched
=CONFIDENCE.NORM(A2,A3,0)	A sample size below 1	#NUM!	#NUM! Provenance Excel documents: "If size < 1, CONFIDENCE.NORM returns the #NUM! error value."	Matched
=CONFIDENCE.NORM("abc",A3,A4)	A non-numeric alpha argument	#VALUE!	#VALUE! Provenance Excel documents: "If any argument is nonnumeric, CONFIDENCE.NORM returns the #VALUE! error value."	Matched

LibreOffice Calc 25.8.7.3 (tested 2026-08-31)

Formula	Description	Result	Expected	Verdict
=ROUND(CONFIDENCE.NORM(A2,A3,A4),9)	Microsoft's documented worked example: 95% confidence half-width for a population standard deviation of 2.5 and a sample of 50	0.692951912	0.692951912 Provenance Microsoft's CONFIDENCE.NORM page publishes this example's result rounded to 0.692952; its CONFIDENCE page publishes the identical calculation to more digits as 0.692951912, and the two agree. Independently derived from the documented normal-distribution half-width z_(1-alpha/2) * standard_dev / sqrt(size): scipy.stats.norm.isf(0.05/2) = 1.9599639845400545, so 1.9599639845400545 * 2.5 / sqrt(50) = 0.6929519121748391 -> 0.692951912 at 9 dp. Asserted at 9 dp rather than the page's 6 because the deeper figure is derived, not merely copied	Matched
=ROUND(CONFIDENCE.NORM(A2,A3,50.9),9)	A non-integer sample size, which the documentation says is truncated	0.692951912	0.692951912 Provenance Excel documents "If size is not an integer, it is truncated", so 50.9 must behave exactly as 50. Independently checked that this discriminates: a genuine size of 50.9 would give 1.9599639845400545 * 2.5 / sqrt(50.9) = 0.686798	Matched
=CONFIDENCE.NORM(1,A3,A4)	A significance level of exactly 1	#VALUE!	#NUM! Provenance Excel documents: "If alpha <= 0 or alpha >= 1, CONFIDENCE.NORM returns the #NUM! error value."	Mismatch
=CONFIDENCE.NORM(A2,-1,A4)	A negative population standard deviation	#VALUE!	#NUM! Provenance Excel documents: "If standard_dev <= 0, CONFIDENCE.NORM returns the #NUM! error value."	Mismatch
=CONFIDENCE.NORM(A2,A3,0)	A sample size below 1	#VALUE!	#NUM! Provenance Excel documents: "If size < 1, CONFIDENCE.NORM returns the #NUM! error value."	Mismatch
=CONFIDENCE.NORM("abc",A3,A4)	A non-numeric alpha argument	#VALUE!	#VALUE! Provenance Excel documents: "If any argument is nonnumeric, CONFIDENCE.NORM returns the #VALUE! error value."	Matched

Docs & syntax

Excel (desktop): official documentation
Google Sheets: official documentation
LibreOffice Calc: official documentation